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General diagnostic imaging software stores, displays and manipulates images, for example PACS viewers, 3D reconstruction or measurement tools operated by the user. Radiology AI adds automated analysis that produces its own output, such as a detection, triage flag or quantitative result.

The distinction matters for evaluation:

• Viewing and processing tools are judged mainly on image quality, usability and integration.
• AI analysis tools also need evidence on accuracy, populations studied, failure modes and monitoring.

Both can be regulated medical devices depending on intended use; in the US many image management and processing functions fall under device classifications. Many vendors now combine the two, so ask which functions are AI-based and which are covered by a regulatory authorization.

AI image reconstruction and denoising use deep learning to produce clearer images from raw scanner data or to reduce noise and artifacts, for example in CT or MRI. Vendors often position these tools as supporting lower-dose or faster scanning protocols.

Unlike detection software, these tools change the image the clinician reads rather than adding a finding. Questions to ask include:

• Is the function built into the scanner or a separate software product?
• Which scanners, protocols and body regions is it authorized for?
• How was diagnostic image quality evaluated, and could fine detail be lost or altered?

These functions are typically regulated as part of the imaging device or as image processing software, depending on the product and market.

AI triage software analyzes incoming imaging studies and flags those that may contain a time-sensitive finding so clinicians can review them sooner, for example by moving a study up the worklist or sending a notification.

In the US, FDA has a device classification for radiological computer-aided triage and notification software (21 CFR 892.2080). As described in that regulation, such a device notifies clinicians of time-sensitive images, does not mark the finding on the original image, does not remove cases from the reading queue, and operates in parallel with the standard of care.

Triage is therefore not a diagnosis: every study still needs to be read. When evaluating triage tools, ask about the target findings, notification workflow and how missed cases are handled.